I Stopped Chasing AI Tools and Started Building AI Spaces, Here's What I Learned
This is a critical change in how we should think about AI. A model alone is like an isolated cognitive process—capable of specific computations but limited in scope. A system is more like the integrated cognitive architecture—coordinating multiple processes, maintaining goal awareness, and adjusting its behavior based on context and feedback. This ... See more
Helen Edwards • The Evolution of AI: From Models to Agents to Social Intelligence
Building effective agents
anthropic.com
I share this sentiment (from Cristobal Valenzuela, founder of RunwayML), on AI and creativity:
... See moreThe most significant gap in AI research and art does not lie within the models themselves but rather in the approach to art. I have noticed a tendency to oversimplify the creative act. In a research setting, the goal is to control and measure variables, wh
Throughout this post, I’ve shared patterns I’ve observed across dozens of AI implementations. The most successful teams aren’t the ones with the most sophisticated tools or the most advanced models – they’re the ones that master the fundamentals of measurement, iteration, and learning.
The core principles are surprisingly simple:
The core principles are surprisingly simple:
- Look at your data.
Hamel Husain • A Field Guide to Rapidly Improving AI Products – Hamel’s Blog
Rather than reaching definitive conclusions about how AI will transform work, I find myself collecting observations about a moving target. What seems consistent is that, for now, the greatest value comes not from surrendering control entirely to AI or clinging to entirely human workflows, but from finding the right points of collaboration for each ... See more
Ethan Mollick • Speaking things into existence
In wrapping up, overcoming the hurdles encountered on the AI path is less about finding immediate solutions and more about adopting a mindset of curiosity, resilience, and continuous learning.